GPU cloud comparison · 2026
Salad vs TensorDock
TensorDock wins on 4 of 5 key metrics — but the right choice depends on your workload.
Salad
Distributed inference cloud — RTX 3090/4090 from $0.03/h
from $0.03/h
★★★★☆ 3.9 / 5 (423 reviews)
Try Salad →VS
Overall Winner
TensorDock
Marketplace GPU cloud — RTX 4090 from $0.21/h, H100 from $1.99/h
from $0.21/h
★★★★☆ 4.2 / 5 (167 reviews)
Try TensorDock →Head-to-Head Comparison
Salad
TensorDock
Starting Price Lower hourly rate
from $0.03/h
from $0.21/h
Overall Rating User rating
3.9 / 5
4.2 / 5
GPU Types Variety
4 types
5 types
Max VRAM Largest available
24 GB
80 GB
Locations Regions covered
Global (distributed)
US, EU, Global
Wins out of 5
1
4
GPU Availability
Salad
RTX 3090RTX 4090RTX 3080RTX 3070
VRAM: 8–24 GB · Locations: Global (distributed)
TensorDock
RTX 4090RTX 3090A100 80GBH100L40S
VRAM: 24–80 GB · Locations: US, EU, Global
Pros & Cons
Salad
Pros
- Absurdly cheap — RTX 3090 from $0.03/h
- Massive horizontal scale (1000+ nodes)
- Auto-fleet management for inference
- No data-egress charges
Cons
- Distributed = no persistent storage
- Not suitable for training
- Latency varies by node geography
TensorDock
Pros
- Among the cheapest H100 access in 2026
- Wide host network = better availability
- Per-second billing for short jobs
- Free egress saves on data-heavy workloads
Cons
- Reliability varies by host
- No managed cluster orchestration
- Support is community-led
Which Should You Choose?
Choose Salad if…
- You need GPU compute for Stateless inference
- You need GPU compute for Stable Diffusion bulk generation
- You need GPU compute for Embedding generation
- You need GPU compute for Cost-sensitive batch jobs
- Lower price is your top priority (from $0.03/h vs from $0.21/h)
Choose TensorDock if…
- You need GPU compute for Budget GPU rentals
- You need GPU compute for Stable Diffusion fine-tuning
- You need GPU compute for Short-burst training
- You need GPU compute for Indie ML developers
- Higher user satisfaction matters (4.2 vs 3.9)
- You want more GPU variety (5 vs 4 types)